Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
74
Ornith-1.0-397B
96
Verified leaderboard positions: GLM-5.1 #30 · Ornith-1.0-397B unranked
Pick Ornith-1.0-397B if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+12.2 difference
Coding
+21.5 difference
GLM-5.1
Ornith-1.0-397B
$1.4 / $4.4
$0 / $0
N/A
N/A
N/A
N/A
203K
262K
Pick Ornith-1.0-397B if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 96 to 74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ornith-1.0-397B's sharpest advantage is in coding, where it averages 82.4 against 60.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 77.5%.
GLM-5.1 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-397B. That is roughly Infinityx on output cost alone. Ornith-1.0-397B gives you the larger context window at 262K, compared with 203K for GLM-5.1.
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 96 to 74. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 77.5%.
Ornith-1.0-397B has the edge for coding in this comparison, averaging 82.4 versus 60.9. GLM-5.1 stays close enough that the answer can still flip depending on your workload.
Ornith-1.0-397B has the edge for agentic tasks in this comparison, averaging 77.5 versus 65.3. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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